Evaluation and prediction of physical development of peri-urban spaces based on CA-MARKOV model (Case study: Torbat Heydarieh city)

Introduction:

Urbanization is one of the consequences of the industrial revolution. One of its main results is land use changes and uneven growth of urban areas, this is one of the main challenges of urban management in the 21st century (Esadi et al., 1400: 143). Therefore, Markov chain analysis is used to predict land use changes in different periods of time. This method is a tool for modeling land and land cover changes. which, taking into account the time probabilities of the intended uses, determines how much the uses have changed at that time (Ata et al., 2016: 15).



Therefore, considering the importance of the research problem, it is necessary to investigate the effects of population increase and its effect on land use changes in the city under study. What distinguishes this research from previous studies is the use of remote sensing technology and the investigation of the effects of urban growth on land use changes. According to the main purpose of the research, the following questions are asked: According to the satellite images, what is the rate of land use changes between the years (1986 to 2020) in the city of Torbat Heydarieh? How much has the increase in population and urban leap between the years (2020 to 1986) affected land use changes in Torbat Heydarieh city? What will be the amount of land use changes in this city until the horizon of 2026?



Research Methodology:

This research in terms of practical purpose and descriptive-analytical nature, and by using library and documentary methods and articles related to the research topic and collecting information and taking satellite images from the USGS site using the OLI sensor in Landsat 8 and the TM sensor in Landsat 5 was conducted between 1986-2013 and 2020 in the city of Torbat Heydarieh. To output the maps from Sanjande (TM & OLI), first the city limits are cut with the Extract by mask command in the Arc Map software. Then, the relevant layers have been classified into 4 classes (residential areas, garden and forest areas, vegetation and grass and wastelands) within the limits of this city with the supervised classification method. NDVI index is used to calculate vegetation changes. In order to predict land changes until the year (2026), TERRSET software has been used using the CA-MARKOV model.



Discussion and findings:

To calculate land uses and land changes between 1986-2013-2020 based on Landsat 8 and 5 satellite images, the amount of land use area in 4 classes (residential areas - garden and forest areas - vegetation and grass - barren lands) using It was extracted from the supervised classification in Arc Map software. The amount of land use changes in 1986 is that according to the population in this year, this city had more garden lands and vegetation. In 2013, with the increase of population towards the north, the area of the city was 21.725,150 square kilometers, which has increased compared to 1986. The area of the city in 2020 has increased by (25.765259) square kilometers compared to previous years. As a result of the increase in the area of the city, the vegetation and garden areas have decreased. The NDVI index and vegetation changes in the years 1986-2013 showed that the amount of land and vegetation changes in 2020 has increased and the increase in man-made areas has caused a decrease in vegetation in the city. The transformation matrix of the land use situation showed that with the increase of changes in the time period (1986-2020), the amount of vegetation and gardens decreased, but residential areas increased. Therefore, the highest percentage of the area of the possibility of land use conversion in the period of 1986-2013 is related to barren lands and the lowest area is related to garden lands. The most probable area of land use conversion status in the period of 1986-2020 is related to barren lands and the least area is related to residential areas. According to the prediction of land changes in TERRSET software in the years 1986 to 2020 with the Markov command, the prediction of changes until the horizon of 2026 was obtained through the CA-Markov command. As a result, the area of residential uses is always increasing. This has caused the reduction of vegetation and garden lands. Therefore, the changes in the area of residential areas until 1405 reach (25.1703) percent.



Conclusion:

This research was conducted with the aim of evaluating urban growth and predicting land changes based on the CA-MARKOV model in the city of Torbat Heydarieh. The results of the prediction of land use changes until 2026 (1405) show that residential areas with an area of (25,170,300) square meters have had the most changes compared to garden and vegetation areas. Therefore, the results of this research are consistent with the results of Ismailpour et al. (2017) in Arak city, and Obayat et al. (2019) in Ahvaz city. By predicting the results of the research using the Markov chain, we can reach this conclusion; With the increase in population until the time horizon of 1405, it is predicted that with the increase in population and the development of the city, in the not too distant future, we will see the destruction of forest lands, gardens, vegetation and agricultural lands in this city and their transformation into residential and man-made areas. Was. Therefore, the innovative aspect of the research is in this, using remote sensing technology and analyzing satellite images and comparing their data in three time periods in different years, first of all, we should pay attention to the increasing migrations and the growth of the city. , physical development and horizontal and vertical growth of the city is evaluated. In the sense that the city should not only increase horizontally, but due to the increase in high-rise construction, clustering and apartment construction, the amount of changes caused by them should be investigated. Therefore, it is suggested to develop the city towards its east and south. To prevent excessive growth and unauthorized construction.